It is not uncommon for businesses to expend significant amounts of money and resources to maximize the performance of employees. This is especially true for employees who may impact the reputation of a business by dealing directly with its customers. For example, many businesses operate or contract customer service centers (e.g., call centers) to provide services to customers. The customer service centers typically employ agents to interface with customers and/or potential customers by way of telephone calls, e-mail messages, or other forms of communication. Because of the direct communication between customer service agents and customers, the agents are in positions that may significantly influence the reputation of a business. Consequently, customer service centers spend significant efforts to train their agents to provide effective and timely customer service.
The skill, training, motivation, and performance of call center agents are significant factors that contribute to the success of a call center. In particular, the profitability of a call center is influenced by the quality of customer service provided by agents, as well as by the volume of interactions handled by the agents. Unfortunately, many agents are unaware of the extent to which they influence the success of a call center. Specifically, agents are typically unaware of the real-time performance levels required to cover the overhead and profit margins of the call center.
Many technologies have been introduced to help call centers succeed. Examples of such technologies include automated computer systems designed to track statistics of call centers. For example, call analytics such as the number of calls handled, the lengths of the calls, the number of incidents resolved, and the average time to handle incidents are typically tracked by call center systems. These statistics have typically been used by managers to analyze the performance of the call center. For example, managers often use the statistics in periodic performance reviews to help train call agents.
Other technologies have been introduced for using call center statistics to monitor and report the performance of agents. Some such technologies are even designed to provide agents with variable compensation based on the performance levels of the agents. This is intended to motivate the agents to improve their performance levels in order to increase their payouts.
While existing performance management technologies may have helped to automate some performance management tasks, there remains room for improvement. For example, existing performance management technologies are costly. One significant cost of existing technologies results from the difficulties involved in integrating the technologies with existing call center systems. Call center systems typically use a wide variety of native computing platforms, languages, and protocols. Consequently, existing performance management technologies have traditionally required significant investment for integration with call center systems, as well as for maintenance of the integrated technologies. The costs are often significant enough to dissuade small and medium-size call centers from making such an investment.
Moreover, many call centers are reluctant to provide full access to their computing systems, especially when trade secrets and industry know-how are contained in the systems. This poses a significant problem because significant access is required to integrate existing performance management technologies with call center systems.
Because of the difficulties, costs, and complexities involved in the integration of existing performance management technologies, manual entry of call center statistics is still widely used. For example, a call center typically includes several different computing tools for tracking and recording call center statistics. Because the computing tools are often implemented in different computing languages and platforms, many existing performance management technologies cannot be practicably interfaced with all of the different computing tools used in all call centers. As a result, many call centers rely upon manual entry of some statistics for use in existing performance management technologies. Manual entry introduces delays and errors into performance management, thereby preventing real-time performance-based motivation.
Another shortcoming of existing performance management technologies can be described as an inability to maximally motivate agents. In particular, several existing technologies seek to motivate agents by informing them of their performances. While this may help motivate agents to increase performance to some degree, these technologies do not maximize the value that may be provided by agents because the agents are not informed of their performances in a manner that encourages self-motivation to add value to the call center. For example, agents may be informed of their performance statistics (e.g., call volume), but the performance statistics are typically provided in a manner that leaves the agents uninformed as to how their performances immediately affect the success of the call center. To illustrate, agents are not typically informed as to how their performances relate to the overhead, profitability margins, and financial success of a call center. Agents left unaware of their values to the call center typically fall short of consistently adding value to the call center. Thus, existing technologies do not provide performance measurements in a manner that encourages maximum self-motivation among agents.
The above-described shortcomings of existing performance management technologies are highlighted by the continuously high attrition rate of call center agents. Even when call centers provide competitive salaries and traditional performance motivators, call center agents continue to experience high turnover rates. Consequently, call centers are forced to spend additional money to recruit and train new agents. The recruitment and training of rookie agents requires significant expenditures that erode profitability.
At least part of the high turnover rates may be attributable to the failure of call centers and existing technologies to focus on the satisfaction and self-motivation of agents. The attention of many existing call centers has been so focused on pleasing customers or motivating agents through variable compensation and peer comparison that existing performance management technologies have failed to consider the importance associated with providing agents with fulfillment, self-motivation, and satisfaction in a manner that also promotes the attainment of the goals of call centers. More specifically, traditional performance management tools have failed to inform agents of their value to the call center. The traditional tools have also failed to instill in agents the self-motivation to add value to and work for the success of a call center. Consequently, high attrition rates among agents have continued and even increased over the last few years.